DBMS > Databricks vs. MySQL vs. Oracle Berkeley DB
System Properties Comparison Databricks vs. MySQL vs. Oracle Berkeley DB
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|Editorial information provided by DB-Engines|
|Name||Databricks Xexclude from comparison||MySQL Xexclude from comparison||Oracle Berkeley DB Xexclude from comparison|
|Description||The Databricks Lakehouse Platform combines elements of data lakes and data warehouses to provide a unified view onto structured and unstructured data. It is based on Apache Spark.||Widely used open source RDBMS||Widely used in-process key-value store|
|Primary database model||Document store|
|Relational DBMS Key/Value like access via memcached API||Key-value store supports sorted and unsorted key sets|
Native XML DBMS in the Oracle Berkeley DB XML version
|Secondary database models||Document store|
|Developer||Databricks||Oracle since 2010, originally MySQL AB, then Sun||Oracle originally developed by Sleepycat, which was acquired by Oracle|
|Current release||8.0.32, January 2023||18.1.40, May 2020|
|License Commercial or Open Source||Open Source||Open Source GPL version 2. Commercial licenses with extended functionallity are available||Open Source commercial license available|
|Cloud-based only Only available as a cloud service||yes||no||no|
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|Implementation language||C and C++||C, Java, C++ (depending on the Berkeley DB edition)|
|Server operating systems||hosted||FreeBSD|
|Data scheme||Flexible Schema (defined schema, partial schema, schema free)||yes||schema-free|
|Typing predefined data types such as float or date||yes||no|
|XML support Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.||yes||yes||yes only with the Berkeley DB XML edition|
|SQL Support of SQL||with Databricks SQL||yes with proprietary extensions||yes SQL interfaced based on SQLite is available|
|APIs and other access methods||JDBC|
RESTful HTTP API
Proprietary native API
|Supported programming languages||Python|
|.Net Figaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET|
others Third-party libraries to manipulate Berkeley DB files are available for many languages
|Server-side scripts Stored procedures||user defined functions and aggregates||yes proprietary syntax||no|
|Triggers||yes||yes only for the SQL API|
|Partitioning methods Methods for storing different data on different nodes||horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric||none|
|Replication methods Methods for redundantly storing data on multiple nodes||yes||Multi-source replication|
|MapReduce Offers an API for user-defined Map/Reduce methods||no||no|
|Consistency concepts Methods to ensure consistency in a distributed system||Immediate Consistency||Immediate Consistency|
|Foreign keys Referential integrity||yes not for MyISAM storage engine||no|
|Transaction concepts Support to ensure data integrity after non-atomic manipulations of data||ACID||ACID not for MyISAM storage engine||ACID|
|Concurrency Support for concurrent manipulation of data||yes||yes table locks or row locks depending on storage engine|
|Durability Support for making data persistent||yes||yes||yes|
|In-memory capabilities Is there an option to define some or all structures to be held in-memory only.||no||yes||yes|
|User concepts Access control||Users with fine-grained authorization concept no user groups or roles||no|
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|Databricks||MySQL||Oracle Berkeley DB|
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